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Monday, October 31, 2016

As reported by Bloomberg: On Friday evening as the sun descended over the old Hollywood set of “Desperate Housewives,” Elon Musk took to a stage and fired up his presentation about climate change. It was a strange scene, with hundreds of people crowded into the middle of a subtly artificial suburban neighborhood.

It wasn’t until about a minute into the speech that Musk casually let the crowd in on Tesla’s big secret. “The interesting thing is that the houses you see around you are all solar houses,” Musk said. “Did you notice?”

The answer, in short, was no. Like everyone else, I knew we were there to see Musk’s new “solar roof,” whatever that was supposed to mean. But try as I could as we walked in, I didn’t see anything that looked like it could carry an electric current. If anything, the slate and Spanish clay roofs looked a bit too nice for a television set. This is the future of solar, Musk proclaimed. “You’ll want to call your neighbors over and say ‘check out the sweet roof.’ It’s not a phrase you hear often.”

The roof tiles are actually made of textured glass. From most viewing angles, they look just like ordinary shingles, but they allow light to pass through from above onto a standard flat solar cell. The plan is for Panasonic to produce the solar cells and for Tesla to put together the glass tiles and everything that goes along with them. That’s all predicated on shareholders approving the $2.2 billion acquisition of SolarCity, the biggest U.S. rooftop installer, on Nov. 17.

Four things I didn't think were solar cells.

Tesla says the tempered glass is “tough as steel,” and can weather a lifetime of abuse from the elements. It can also be fitted with heating elements to melt snow in colder climates. “It’s never going to wear out,” Musk said, “It’s made of quartz. It has a quasi-infinite lifetime.”

In a Q&A with reporters after the presentation, Musk said the tiles are comparable to competing high-efficiency solar panels. The current prototypes that Tesla engineers are working with reduce the efficiency of the underlying solar cell by just 2 percent. With further refinement, Musk said he hopes the microscopic louvers responsible for making the tiles appear opaque can be used to actually boost the efficiency of standard photovoltaic cells.

This, apparently, is a solar roof.

Putting the pieces together

The vision presented at Universal Studios in Los Angeles is the grand unification of Musk’s clean-energy ambitions. The audience was able to step into a future powered entirely by Tesla: a house topped with sculpted Tuscan solar tiles, where night-time electricity is stored in two sleek wall-hung Powerwall batteries, and where a Model 3 prototype electric car sits parked out front within reach of the home’s car charger.

Attracting less attention on Wisteria Lane was Tesla’s Powerwall 2, a major upgrade of its home battery for electricity storage. When the original Powerwall was released last year, I was skeptical. Mostly, it was just too pricey for the amount of power it provided, especially in the U.S. where electricity is cheap and most people can sell their excess solar power back to the grid. Version 2 is a much different product. It packs more than twice the capacity—14 kilowatt hours versus 6.4 kilowatt hours—for less than half the price after installation. 1 It includes a built-in Tesla-brand inverter and comes with a ten year, infinite-cycle warranty.

More power to ya.

Photographer: Tom Randall/Bloomberg

Electricity storage is crucial for future uptake of solar power. Already in some solar-heavy regions, more electricity is being produced during the middle of the day than people can consume, and utility prices spike in the evening hours when the sun goes down. In the U.S., some states are abandoning payments for daytime rooftop solar, undermining huge investments that families have made in their solar systems. The only recourse is for customers to use that electricity themselves, at night.

Like previous attempts at solar shingles, the solar-plus-battery package hasn’t really caught on yet. SolarCity’s total bundled sales thus far number in just the hundreds. But an argument can be made that the products just weren't compelling enough yet and the prices were still too high.

The Powerwall 2 may be the cheapest lithium ion battery for the home ever made when deliveries start in January. Tesla is selling the batteries at retail prices that are cheaper than the average manufacturing cost at most companies, according to data compiled by Bloomberg New Energy Finance. We "certainly expect it will move the market prices downwards as we saw last year with the first Powerwall," said Yayoi Sekine, a BNEF analyst who covers battery technology.

“The future is going to overwhelmingly be solar plus battery,” Musk said. "They go together like peanut butter and jelly."

Source: Bloomberg New Energy Finance

Let’s wait and see

Powerwall 2 looks ready for primetime. The new solar shingles? Let’s wait until more details emerge. Tesla says we should expect a slow initial rollout beginning in about nine months. Within two years of production, the shingles could account for five percent of the five million roofs installed in the U.S. every year, said Peter Rive, SolarCity’s co-founder and chief technology officer. SolarCity, under the Tesla brand, would also continue to sell surface-mounted solar panels for homeowners who have no plans for replacing their existing roofs.

The pricing on the new solar roof is a bit—squishy. Musk said that someone who buys a Tesla roof will save money compared with someone who buys a comparable traditional roof plus electricity from the grid. But make no mistake: This will be a premium product, at least when it first rolls out. The terra cotta and slate roofs Tesla mimicked are among the most expensive roofing materials on the market. SolarCity CEO Lyndon Rive noted that the price of a conventional roof can vary widely, from $7,000 to $70,000—based on materials, size, complexity, location—so giving out firm prices of a solar roof at this point would be difficult.

Telsa will release more financial information about the SolarCity deal this week before it goes to shareholders for a vote. If all of Musk's plans come true, by the end of next year you'll be able to walk into a Tesla store, buy a Model 3 electric car, a slate-glass solar roof, and a Powerwall 2 to manage the flow of all those electrons in your life. There are a lot of details to be hammered out until we know for certain whether Musk’s vision for a grand unification will become more than just a great television backdrop. But these tiles, viewed up close, are definitely worth tuning in for.

The requests came from what are called expert networks—research firms that connect investors with people who can help them understand particular markets and provide a competitive edge (sometimes, it seems, through insider information). These expert networks wanted me to explain how Google’s AI processor would affect the chip market. But first, they wanted me to sign a non-disclosure agreement. I declined.

These unsolicited, extremely specific, high-pressure requests—which arrived about three week ago—underscore the radical changes underway in the enormously lucrative computer chip market, changes driven by the rise of artificial intelligence. Those hedge fund managers see these changes coming, but aren’t quite sure how they’ll play out.

Of course, no one is quite sure how they’ll play out.

Today, Internet giants like Google, Facebook, Microsoft, Amazon, and China’s Baidu are exploring a wide range of chip technologies that can drive AI forward, and the choices they make will shift the fortunes of chipmakers like Intel and nVidia. But at this point, even the computer scientists within those online giants don’t know what the future holds.

Going Deep

These companies run their online services from data centers packed with thousands of servers, each driven by a chip called a central processing unit, or CPU. But as they embrace a form of AI called deep neural networks, these companies are supplementing CPUs with other processors. Neural networks can learn tasks by analyzing vast amounts of data, including everything from identifing faces and objects in photos to translating between languages, and they require more than just CPU power.

Any choice these companies make matters, because their online operations are so vast. They buy and operate far more computer hardware than anyone else on Earth, a gap that will only widen with the continued importance of cloud computing. If Google chooses one processor over another, it can fundamentally shift the chip industry.

The TPU poses a threat to companies like Intel and nVidia because Google makes this chip itself. But GPUs also play an enormous role within Google and its ilk, and nVidia is the primary manufacturer of these specialized chips. Meanwhile, Intel has inserted itself into the mix by acquiring Altera, the company that sells all those FPGAs to Microsoft. At $16.7 billion, it was Intel’s largest acquisition ever, which underscores just how much the chip market is changing.

First, Training. Then, Execution

But sorting all this out is difficult—in part because neutral networks operate in two stages. The first is the training stage, where a company like Google trains the neural network to perform a given task, like recognizing faces in photos or translating from one language to another. The second is the execution stage, where people like you and me actually use the neural net—where we, say, post a photo of our high school reunion to Facebook and it automatically tags everyone in it. These two stages are quite different, and each requires a different style of processing.

Today, GPUs are the best option for training. Chipmakers designed GPUs to render images for games and other highly graphical applications, but in recent years, companies like Google discovered these chips can also provide an energy-efficient means of juggling the mind-boggling array of calculations required to train a neural network. This means they can train more neural nets with less hardware. Microsoft AI researcher XD Huang calls GPUs “the real weapon.” Recently, his team completed a system that can recognize certain conversational speech as well as humans, and it took them about a year. Without GPUs, he says, it would have taken five. After Microsoft published a research paper on this system, he opened a bottle of champagne at the home of Jen-Hsun Huang, the CEO of nVidia.

But companies also need chips that can rapidly execute neural networks, a process called inference. Google built the TPU specifically for this. Microsoft uses FPGAs. And Baidu is using GPUs, which aren’t as well suited to inference as they are to training, but can do the job with the right software in place.

To the Smartphone

At the same time, others are building chips to help execute neural networks on smartphones and other devices. IBM is building such a chip, though some wonder how effective it might be. And Intel has agreed to acquire Movidius, a company that is already pushing chips into devices.

Intel understands that the market is changing. Four years ago, the chip maker told us it sells more server processors to Google than it sells to all but four other companies—so it sees firsthand how Google and its ilk can shift the chip market. As a result, it’s now placing bets everywhere. Beyond snapping up Altera and Movidius, it has agreed to buy a third AI chip company called Nervana.

That makes sense, because the market is only starting to develop. “We’re now at the precipice of the next big wave of growth,” Intel vice president Jason Waxman recently told me, “and that’s going to be driven by artificial intelligence.” The question is where the wave will take us.

Tuesday, October 25, 2016

As reported by Engadget: If you're in Colorado and grab a can of Budweiser, it's possible that you might be sipping beer delivered by Uber's autonomous truck company. Today, Otto confirmed that on October 20th, it "completed the world's first shipment by a self-driving truck," a delivery that involved transporting 2,000 cases (or 51,744 cans) of Bud from Fort Collins, Colorado to Colorado Springs along Interstate 25.

Although impressive, this "world first" is mostly promotional. The Verge reports that a human driver first navigated the truck from a Anheuser-Busch depot to a weigh station in Fort Collins. From there, Otto's self-driving technology was deployed and the Volvo big rig drove the remaining 100 miles to Colorado Springs without any outside assistance. Once it entered the city, the driver -- who monitored the journey from the sleeper berth in the back -- resumed control and completed the final maneuvers.

With Uber's self-driving cars taking to US streets and Otto now starting to make its first shipments, the company is finally starting to realize its vision as a logistics company. Right now, deliveries are marketed as a step towards a "safe and productive future" across US highways, allowing drivers to rest while their vehicle does the hard miles. However, with Uber's rapid expansion into cities worldwide, it likely won't be long until it's self-driving trucks can negotiate confusing inter-city streets too.

To mark the Budweiser milestone, Uber is now inviting potential partners to inquire about its haulage offering, which it's now calling Uber Freight. "Our partnership with Anheuser-Busch is just beginning," says the company in a blog post. "Our companies are excited to transform commercial transportation together."

But, before Teslas can start driving autonomously, the company needs to collect a lot of data to prove to customers (and regulators) that the technology is safe and reliable. So, the car will run Autopilot in “shadow mode” in order for Tesla to gather statistical data to show false positives and false negatives of the software. In shadow mode, the car isn’t taking any action, but it registers when it would have taken action. Then, if the Tesla is in an accident, the company can see if the autonomous mode would have avoided the accident (or the other way around, with the self-driving system potentially causing an accident).

It will record how the car would have acted if the computer was in control, including information about how the car might have avoided an accident (or caused one). That data would then be used to show “a material improvement in the accident rate over manually driven cars,” said Tesla CEO Elon Musk on a call with reporters today. “I think at that point regulators would be comfortable approving it.”

Musk said that he hopes the US will not end up with a patchwork of autonomous regulations across states, noting that the EU appears like it will have a unified standard. He hopes that Tesla’s collection of statistical data regarding potential autonomous vehicle actions — millions of miles across thousands of cars driving in the real world — will help regulators be comfortable enough to sign off on his self-driving vision.

“We look carefully at the regulations and make sure that what we do is in line with those,” Musk said. “We can’t do anything other than that because it would be against the law.”

Tesla also announced it is giving all its new cars the hardware for “full self-driving capabilities,” including 8 cameras with 360-degree viewing at up to 820 feet of distance, as well as 12 ultrasonic sensors that can detect both hard and soft objects. A new forward-facing radar helps see through rain, fog, and dust.

“The full autonomy update will be standard on all Tesla vehicles from here on out,” Musk says.

The updates are included in all new Tesla vehicles built from today forward — however, don’t expect your new Model X to be fully autonomous when you pick it up. Tesla says it needs to “further calibrate the system using millions of miles of real-world driving” before it hands your car fully over to a computer.

On the call about the new hardware, Musk said the hardware is fully capable of “Level 5 autonomy,” a big step forward.

Most significantly, new Teslas won’t have access to some safety features that older Teslas have, including automatic emergency braking, collision warning, lane holding, and active cruise control. The company says that these features will be activated after they are “robustly validated.”

“As always, our over-the-air software updates will keep customers at the forefront of technology and continue to make every Tesla, including those equipped with first-generation Autopilot and earlier cars, more capable over time,” said the Tesla statement.

In essence, it reads as though Tesla has put together a better, more powerful hardware system for these safety and autonomous driving features, but this new system isn’t going to be ready for real use right away. That’s a disappointing dip in the road, but apparently a necessary one.

Musk started off the call with a testy answer - defending Tesla Autopilot and laying into media outlets that don’t put the accidents that have happened from it into the proper context. Autonomous driving is so much safer, Musk argues, that outlets that put too much emphasis on the crash are “killing people.” He then added: “next question.”Musk says that the “Tesla Neural Net” doesn’t require any third party hardware sensors, and that it’s based on the Nvidia Titan GPU (although it could run on other processors). He says that it’s 40 times more powerful than the last Tesla computer, “it’s basically a supercomputer in a car,” he said. “We go from one camera to eight cameras,” Musk said. Three of them are forward cameras, for redundancy, and the rest provide “360 coverage” for the rest of the car. The new Teslas will also have 360-ultrasonic sonar.“I think is is very hard to turn into a kit,” Musk said, so it won’t be sold to other car makers. All the cameras and sensors he is talking about won’t cause “weird protuberances” or make the cars look funny.Musk also promised a demonstration of a fully autonomous drive from Los Angeles to New York by the end of 2017. Musk largely begged off talking about what the regulation would or should be but he did note that the computer will “always be running in ‘shadow mode,’” so that he can build the case that his self-driving software would have been safer than human drivers.Fully-autonomous Teslas are getting closer to reality. Yesterday, the electric carmaker announced that all new vehicles will come with extra hardware to support "full self-driving capabilities,” and this morning, the company posted a video showing exactly what that hardware can do.The self-driving software is not finished and has yet to be approved by regulators, but the four-minute clip is nonetheless impressive, showing a Tesla leaving a garage, driving across town, and finding its own parking spot — all autonomously. There is someone sat in the driver's seat, as per current legal requirements, but they never touch the wheel. Tesla CEO Elon Musk, who posted the clip to Twitter, notes that the car is even smart enough to driver past a disabled parking spot, knowing it's not allowed to park there. He also highlighted the car's summon function:

All of this technology is a long way from being implemented, but it does raise some interesting questions. Like, what happens if you summon a Tesla on your phone while you are moving (say on a train, or in another form of transportation like a taxi) — will the car follow you round indefinitely, or will it only drive to the initial summon location? It's all to come.

Wednesday, October 19, 2016

As reported by Spectrum IEEE: Idling in rush-hour traffic can be mind numbing. It also carries other costs. Traffic congestion costs the U.S. economy $121 billion a year, mostly due to lost productivity, and produces about 25 billion kilograms of carbon dioxide emissions, Carnegie Mellon University professor of robotics Stephen Smith told the audience at a White House Frontiers Conference last week. In urban areas, drivers spend 40 percent of their time idling in traffic, he added.

The big reason is that today’s traffic signals are dumb. Smith is developing smart artificial-intelligence-fueled traffic signals that adapt to changing traffic conditions on the fly. His startup Surtrac is commercializing the technology.

In pilot tests in Pittsburgh, the smart traffic management system has gotten impressive results. It reduced travel time by 25 percent and idling time by over 40 percent. That means less time spent staring out the windshield and more time working, being with your family, or doing anything else. I’m a Pittsburgh resident who has witnessed the city’s rapidly-evolving urban landscape. And I can attest to the mostly frustration-free driving that has resulted from this system despite a the city’s growing population.

The researchers also estimate that the system cuts emissions by 21 percent. It could also save cities the cost of road-widening or eliminating street parking by boosting traffic throughput.

Conventional traffic lights have preprogrammed timing that’s updated every few years. But as traffic patterns evolve, the systems can fall out of date much more quickly that.

The Surtrac system instead relies on computerized traffic lights coordinating closely with each other. Radar sensors and cameras at each light detect traffic. Sophisticated AI algorithms use that data to build a timing plan “that moves all the vehicles it knows about through the intersection in the most efficient way possible,” Smith says. The computer also sends the data to traffic intersections downstream so they can plan ahead.

Unlike other smart traffic-management systems, such as one used in Los Angeles, Smith emphasized that this one is decentralized. So each signal makes its own timing decisions, making it a truly smart system.

Smith’s team started by implementing the AI traffic control system at nine intersections in Pittsburgh’s busy East Liberty neighborhood in 2012. The network now spans 50 intersections, with plans to expand it city-wide.

The next step is to have traffic signals talk to cars. The Smith’s group has already installed short-range radios at 24 intersections. Such systems are expected to begin being built into some cars in 2017, he said. Traffic signals could then let drivers know of upcoming traffic conditions or let them know lights are about to change, increasing safety and relieving congestion.

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About Me

I have more than 25 years of experience in development, design, and mobile communications products and technology. I also enjoy skiing, hiking, scuba, tennis, reading, traveling, foreign languages, and painting. I'm an active member of the National Ski Patrol (NSP) and volunteer my time at either Loveland Ski resort, or Ski Cooper.